Vehicle Activity Notification System Using Contextual Signal Analysis
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Solution Overview
Problem
Current driving safety applications lack real-time detection and notification capabilities, particularly for new drivers or situations like accidents or vehicle issues, and struggle with generating accurate contextual determinations from limited signal data.
Innovation Solution
A trained AI model is used to analyze signal data from a mobile device onboard a vehicle to generate activity determinations and automatically provide graphical user interface (GUI) notifications to users, including emergency contacts, with features for customizable notifications and summary reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional driving safety applications focus on historical determinations, then they can analyze past driving behavior, but they cannot provide real-time detection and notification of vehicle activity
Solution Approach 1:
The system performs preliminary actions by collecting and storing multiple types of signal data (GPS location, accelerometer, gyroscope, magnetometer, barometer) before an event occurs. This pre-collection of data enables both rapid real-time detection and thorough subsequent analysis, resolving the contradiction between speed and reliability
Solution Approach 2:
The patent transitions from two-dimensional historical analysis to multi-dimensional real-time analysis by incorporating spatial (GPS), temporal (timestamp), and sensory (accelerometer, gyroscope, magnetometer, barometer) dimensions. This multi-dimensional approach enables simultaneous real-time detection and accurate determination
2Measurement precision
If traditional applications analyze only a small number of signals, then they can process data quickly, but they cannot generate accurate contextual determinations of vehicle activity
Solution Approach 1:
The system segments the complex analysis task into distinct modules: GPS location analysis, accelerometer detection, gyroscope analysis, magnetometer reading, and barometer measurement. Each segment processes specific signal types independently, then integrates results to achieve high measurement precision without overwhelming system complexity
Solution Approach 2:
The mobile computing device serves multiple functions simultaneously - it acts as GPS receiver, accelerometer, gyroscope, magnetometer, and barometer. This multi-functionality allows comprehensive signal analysis without requiring separate dedicated hardware for each sensor type, managing complexity while maintaining precision
3Extent of automation
If no automatic notification system is implemented, then the system remains simple, but users cannot receive instantaneous notifications about vehicle activity
Solution Approach 1:
The system implements self-service automation where the mobile computing device automatically detects vehicle activity, determines the context using trained models, and sends notifications to designated contacts without requiring manual user intervention. This automation is achieved through pre-configured rules and machine learning models that enable the system to serve itself
Solution Approach 2:
The system incorporates feedback mechanisms where notification delivery status and user responses are tracked and used to refine future notification behavior. This feedback loop enables the automated notification system to adapt and improve while maintaining manageable complexity through data-driven optimization
Data Source
AI summary
The present disclosure that relates to automatic generation of activity determinations of a vehicle and generation and provision of notifications thereof. As an example, a trained model is applied that is adapted to execute a contextual analysis of signal data, including activity signal data retrieved from analysis of signals provided by a mobile computing device onboard a vehicle, and generate activity determinations therefrom. Exemplary graphical user interface (GUI) notifications can be automatically generated pertaining to activity determinations of a vehicle (vehicle activity determinations), where the GUI notifications can be automatically provided to one or more users. For instance, a GUI notification is automatically provided to an emergency contact of a driver in real-time (or near real-time) when it is detected that a vehicle has stopped (e.g., on a specific road such as a highway). Additional examples of the present disclosure pertain to an improved GUI for a driving safety application/service.